1. Background Field
Embodiments of the subject matter described herein are related generally to adding target images to search trees stored in a database, and more specifically for determining whether a new target image should be added to the search tree.
2. Relevant Background
Object recognition typically uses an object database that is searched based on an image of the object. Typically, the object database has a search tree structure, such as the well-known k-d trees, HK means tree, and vocabulary trees. A useful object database should include many searchable objects and, thus, object databases tend to be large. Moreover, new objects may be added to object databases automatically, which typically requires a re-balancing of the search tree, i.e., the tree structure of the search tree is changed based on the newly included object. Re-balancing the search tree is a resource intensive operation. However, if the new object is not good for object recognition or if the performance of the object database deteriorates with the inclusion of the new object, then the addition of the new object to the search tree is undesirable. Thus, it is desirable to determine how the performance of the object database will be affected by the inclusion of a new object before that object is added to the database to avoid unnecessarily re-balancing the search tree.